Fingerprint Analysis(part 2)

Pavel Mrázek

Local ridge frequency

Local ridge frequency

Image enhancement / binarization• General rule:

– Smooth along ridges– Enhance ridge-valley contrast– Separate fingerprint from background

(segmentation)

• Various methods: – Convolution – PDEs – Morphology – Gabor filters – …

Gabor filters

• Several orientations• Several frequencies

• At each position,– select orientation– select frequency– filter using the appropriate Gabor filter

Gabor filters

Coherence enhancing shock filter

• Shock filter:

• Regularized:

Coherence enhancing shock filter

• Use direction estimate:w … dominant eigenvector of the structure tensor

Examples

Coherence enhancing shock filter

Ridge thinning• Thinning: morphological operation

• Pixel value set to background if ridge connectivity not affected

• Structuring element: typically 3x3 window

• 9 pixels, 512 possible configurations, look-up

Singular point detection• Methods for core and delta detection:

– Poincaré index– Irregularity of orientation field, curvature– Partitioning of orientation field

• Reliability problems

Texture features

Feature extraction summaryExtract features, store a template

• Prepare representation useful for matching– minutiae– …

• Reduce memory requirements(typical size 500 B – 30 kB)

• Privacy: fingerprint not stored

Enrollment• Register user, store data into a

database

Verification• Compare to enrolled template,

accept / reject a match

Identification• Recover identity, 1-to-N match

References• Maltoni et al.: Handbook of Fingerprint Recognition. Springer

2003.• Maltoni. A tutorial on fingerprint recognition. In LNCS 3161,

Springer 2005.• Hong, Wan, Jain. Fingerprint image enhancement: algorithm

and performance evaluation. IEEE PAMI 1998.• Zhou, Gu. A model-based method for the computation of

fingerprints’ orientation field. IEEE TIP 2004.• Weickert. Coherence enhancing shock filters. DAGM 2003.

• Contact: mrazekp -at- cmp.felk.cvut.cz